Prediction of prostate tumour hypoxia using pre-treatment MRI-derived radiomics: preliminary findings.

PURPOSE: To develop a machine learning (ML) model based on radiomic features (RF) extracted from whole prostate gland magnetic resonance imaging (MRI) for prediction of tumour hypoxia pre-radiotherapy. MATERIAL AND METHODS: Consecutive patients with high-grade prostate cancer and pre-treatment MRI treated with radiotherapy between 01/12/2007 and 1/08/2013 at two cancer centres were included. Cancers were dichotomised as normoxic or hypoxic using a biopsy-based 32-gene hypoxia signature (Ragnum signature). Prostate segmentation was performed on axial T2-weighted (T2w) sequences using RayStation (v9.1). Histogram standardisation was applied prior to RF extraction. PyRadiomics (v3.0.1) was used to extract RFs for analysis. The cohort was split 80:20 into training and test sets. Six different ML classifiers for distinguishing hypoxia were trained and tuned using five different feature selection models and fivefold cross-validation with 20 repeats. The model with the highest mean validation area under the curve (AUC) receiver operating characteristic (ROC) curve was tested on the unseen set, and AUCs were compared via DeLong test with 95% confidence interval (CI). RESULTS: 195 patients were included with 97 (49.7%) having hypoxic tumours. The hypoxia prediction model with best performance was derived using ridge regression and had a test AUC of 0.69 (95% CI: 0.14). The test AUC for the clinical-only model was lower (0.57), but this was not statistically significant (p = 0.35). The five selected RFs included textural and wavelet-transformed features. CONCLUSION: Whole prostate MRI-radiomics has the potential to non-invasively predict tumour hypoxia prior to radiotherapy which may be helpful for individualised treatment optimisation.

Radiotherapy respiratory motion management in hepatobiliary and pancreatic malignancies: a systematic review of patient factors influencing effectiveness of motion reduction with abdominal compression.

BACKGROUND: The effectiveness of abdominal compression for motion management in hepatobiliary-pancreatic (HPB) radiotherapy has not been systematically evaluated. METHODS & MATERIALS: A systematic review was carried out using PubMed/Medline, Cochrane Library, Web of Science, and CINAHL databases up to 1 July 2021. No date restrictions were applied. Additional searches were carried out using the University of Manchester digital library, Google Scholar and of retrieved papers' reference lists. Studies conducted evaluating respiratory motion utilising imaging with and without abdominal compression in the same patients available in English were included. Studies conducted in healthy volunteers or majority non-HPB sites, not providing descriptive motion statistics or patient characteristics before and after compression in the same patients or published without peer-review were excluded. A narrative synthesis was employed by tabulating retrieved studies and organising chronologically by abdominal compression device type to help identify patterns in the evidence. RESULTS: The inclusion criteria were met by 6 studies with a total of 152 patients. Designs were a mix of retrospective and prospective quantitative designs with chronological, non-randomised recruitment. Abdominal compression reduced craniocaudal respiratory motion in the majority of patients, although in four studies there were increases seen in at least one direction. The influence of patient comorbidities on effectiveness of compression, and/or comfort with compression was not evaluated in any study. CONCLUSION: Abdominal compression may not be appropriate for all patients, and benefit should be weighed with potential increase in motion or discomfort in patients with small initial motion (<5 mm). Patient factors including male sex, and high body mass index (BMI) were found to impact the effectiveness of compression, however with limited evidence. High-quality studies are warranted to fully assess the clinical impact of abdominal compression on treatment outcomes and toxicity prospective in comparison to other motion management strategies.

Comparison of intensity modulated radiotherapy plan optimisation methods for a 1.5 T MR-Linac.

PURPOSE: For the 1.5 T Elekta MR-Linac it is essential that the optimisation of a treatment plan accounts for the electron return effect on the planned dose distribution. The ability of two algorithms for the first stage fluence optimisation, pencil beam (PB) and Monte Carlo (MC), to produce acceptable plan quality was investigated. Optimisation time for each algorithm was also compared. METHODS: Ten head and neck patients, ten lung patients and five prostate patients were selected from the clinical archive. These were retrospectively planned using a research version of Monaco with both the PB and MC algorithms for the fluence optimisation stage. After full optimisation DVH parameters, optimisation time and the number of Monitor Units (MU) as a measure of plan complexity were extracted. RESULTS: There were no clinically significant differences between any of the DVH parameters studied or the total number of MUs between using PB or MC for stage 1 optimisation across the three patient groups. However, planning time increased by a factor of ten using MC algorithms for stage 1. CONCLUSION: The use of MC calculations compared to PB, for stage 1 fluence optimisation, results in increased planning time without clinical improvement in plan quality or reduction in complexity and is therefore not necessary.

Prospective evaluation of relationships between radiotherapy dose to masticatory apparatus and trismus.

AIMS: This feasibility study aimed to identify relationships between radiation doses to the masticatory apparatus as a combined block or as individual subunits with changes in trismus following radiotherapy. MATERIAL AND METHODS: Twenty patients from a single center were recruited prospectively as part of a randomized trial comparing proactive exercises in the management of trismus. Patients with stage III/IV oral cavity or oropharyngeal squamous cell cancers received intensity-modulated radiotherapy with concurrent systemic therapy. All patients had trismus prior to radiotherapy. Maximal inter-incisor distance (MID) was measured pre- and 6 months from the start of radiotherapy. Bilateral muscles of mastication: medial and lateral pterygoids (MP and LP), masseters (M), temporalis (T), temporomandibular joint (TMJ) were contoured on CT images. The block comprised all muscles excluding the TMJ below the orbital floor. Mean dose, equivalent uniform dose (EUD) and V35-V60 Gy were compared with change in MID. RESULTS: In six patients, the MID deteriorated at 6 months from the start of radiotherapy compared with 14 whose MID improved. No significant association was observed between age, gender, smoking, alcohol status, exercise compliance, cisplatin, tumor site, stage, V35-V60 Gy or EUD with change in MID. A clinical outlier was excluded. Without the outlier (n = 19), a significant association was seen between mean dose and change in MID at 6 months for the ipsilateral block (p = .01), LP (p = .04) and M (p < .01). All patients where trismus deteriorated at 6 months received mean doses >40 Gy to the block. CONCLUSION: Higher mean radiation doses to the ipsilateral block, LP and M were significantly associated with deterioration in trismus. Limiting dose to these structures to ≤40 Gy for tumors not invading the masticatory muscles may improve treatment-related sequelae. The ipsilateral block, LP and M should be studied further as possible alternative avoidance structures in radiotherapy treatment planning.

The suitability of common metrics for assessing parotid and larynx autosegmentation accuracy.

Contouring structures in the head and neck is time-consuming, and automatic seg-mentation is an important part of an adaptive radiotherapy workflow. Geometric accuracy of automatic segmentation algorithms has been widely reported, but there is no consensus as to which metrics provide clinically meaningful results. This study investigated whether geometric accuracy (as quantified by several commonly used metrics) was associated with dosimetric differences for the parotid and larynx, comparing automatically generated contours against manually drawn ground truth contours. This enabled the suitability of different commonly used metrics to be assessed for measuring automatic segmentation accuracy of the parotid and larynx. Parotid and larynx structures for 10 head and neck patients were outlined by five clinicians to create ground truth structures. An automatic segmentation algorithm was used to create automatically generated normal structures, which were then used to create volumetric-modulated arc therapy plans. The mean doses to the automatically generated structures were compared with those of the corresponding ground truth structures, and the relative difference in mean dose was calculated for each structure. It was found that this difference did not correlate with the geometric accuracy provided by several metrics, notably the Dice similarity coefficient, which is a commonly used measure of spatial overlap. Surface-based metrics provided stronger correlation and are, therefore, more suitable for assessing automatic seg-mentation of the parotid and larynx.

Assessment of heart-substructures auto-contouring accuracy for application in heart-sparing radiotherapy for lung cancer.

Objectives: We validated an auto-contouring algorithm for heart substructures in lung cancer patients, aiming to establish its accuracy and reliability for radiotherapy (RT) planning. We focus on contouring an amalgamated set of subregions in the base of the heart considered to be a new organ at risk, the cardiac avoidance area (CAA), to enable maximum dose limit implementation in lung RT planning. Methods: The study validates a deep-learning model specifically adapted for auto-contouring the CAA (which includes the right atrium, aortic valve root, and proximal segments of the left and right coronary arteries). Geometric, dosimetric, quantitative, and qualitative validation measures are reported. Comparison with manual contours, including assessment of interobserver variability, and robustness testing over 198 cases are also conducted. Results: Geometric validation shows that auto-contouring performance lies within the expected range of manual observer variability despite being slightly poorer than the average of manual observers (mean surface distance for CAA of 1.6 vs 1.2 mm, dice similarity coefficient of 0.86 vs 0.88). Dosimetric validation demonstrates consistency between plans optimized using auto-contours and manual contours. Robustness testing confirms acceptable contours in all cases, with 80% rated as "Good" and the remaining 20% as "Useful." Conclusions: The auto-contouring algorithm for heart substructures in lung cancer patients demonstrates acceptable and comparable performance to human observers. Advances in knowledge: Accurate and reliable auto-contouring results for the CAA facilitate the implementation of a maximum dose limit to this region in lung RT planning, which has now been introduced in the routine setting at our institution.

Dose-dependent changes in cardiac function, strain and remodelling in a preclinical model of heart base irradiation.

BACKGROUND AND PURPOSE: Radiation induced cardiotoxicity (RICT) is as an important sequela of radiotherapy to the thorax for patients. In this study, we aim to investigate the dose and fractionation response of RICT. We propose global longitudinal strain (GLS) as an early indicator of RICT and investigate myocardial deformation following irradiation. METHODS: RICT was investigated in female C57BL/6J mice in which the base of the heart was irradiated under image-guidance using a small animal radiation research platform (SARRP). Mice were randomly assigned to a treatment group: single-fraction dose of 16 Gy or 20 Gy, 3 consecutive fractions of 8.66 Gy, or sham irradiation; biological effective doses (BED) used were 101.3 Gy, 153.3 Gy and 101.3 Gy respectively. Longitudinal transthoracic echocardiography (TTE) was performed from baseline up to 50 weeks post-irradiation to detect structural and functional effects. RESULTS: Irradiation of the heart base leads to BED-dependent changes in systolic and diastolic function 50 weeks post-irradiation. GLS showed significant decreases in a BED-dependent manner for all irradiated animals, as early as 10 weeks after irradiation. Early changes in GLS indicate late changes in cardiac function. BED-independent increases were observed in the left ventricle (LV) mass and volume and myocardial fibrosis. CONCLUSIONS: Functional features of RICT displayed a BED dependence in this study. GLS showed an early change at 10 weeks post-irradiation. Cardiac remodelling was observed as increases in mass and volume of the LV, further supporting our hypothesis that dose to the base of the heart drives the global heart toxicity.

A joint ESTRO and AAPM guideline for development, clinical validation and reporting of artificial intelligence models in radiation therapy.

BACKGROUND AND PURPOSE: Artificial Intelligence (AI) models in radiation therapy are being developed with increasing pace. Despite this, the radiation therapy community has not widely adopted these models in clinical practice. A cohesive guideline on how to develop, report and clinically validate AI algorithms might help bridge this gap. METHODS AND MATERIALS: A Delphi process with all co-authors was followed to determine which topics should be addressed in this comprehensive guideline. Separate sections of the guideline, including Statements, were written by subgroups of the authors and discussed with the whole group at several meetings. Statements were formulated and scored as highly recommended or recommended. RESULTS: The following topics were found most relevant: Decision making, image analysis, volume segmentation, treatment planning, patient specific quality assurance of treatment delivery, adaptive treatment, outcome prediction, training, validation and testing of AI model parameters, model availability for others to verify, model quality assurance/updates and upgrades, ethics. Key references were given together with an outlook on current hurdles and possibilities to overcome these. 19 Statements were formulated. CONCLUSION: A cohesive guideline has been written which addresses main topics regarding AI in radiation therapy. It will help to guide development, as well as transparent and consistent reporting and validation of new AI tools and facilitate adoption.

Stereotactic Body Radiotherapy for Centrally Located Inoperable Early-Stage NSCLC: EORTC 22113-08113 LungTech Phase II Trial Results.

INTRODUCTION: The international phase II single-arm LungTech trial 22113-08113 of the European Organization for Research and Treatment of Cancer assessed the safety and efficacy of stereotactic body radiotherapy (SBRT) in patients with centrally located early-stage NSCLC. METHODS: Patients with inoperable non-metastatic central NSCLC (T1-T3 N0 M0, ≤7cm) were included. After prospective central imaging review and radiation therapy quality assurance for any eligible patient, SBRT (8 × 7.5 Gy) was delivered. The primary endpoint was freedom from local progression probability three years after the start of SBRT. RESULTS: The trial was closed early due to poor accrual related to repeated safety-related pauses in recruitment. Between August 2015 and December 2017, 39 patients from six European countries were included and 31 were treated per protocol and analyzed. Patients were mainly male (58%) with a median age of 75 years. Baseline comorbidities were mainly respiratory (68%) and cardiac (48%). Median tumor size was 2.6 cm (range 1.2-5.5) and most cancers were T1 (51.6%) or T2a (38.7%) N0 M0 and of squamous cell origin (48.4%). Six patients (19.4%) had an ultracentral tumor location. The median follow-up was 3.6 years. The rates of 3-year freedom from local progression and overall survival were 81.5% (90% confidence interval [CI]: 62.7%-91.4%) and 61.1% (90% CI: 44.1%-74.4%), respectively. Cumulative incidence rates of local, regional, and distant progression at three years were 6.7% (90% CI: 1.6%-17.1%), 3.3% (90% CI: 0.4%-12.4%), and 29.8% (90% CI: 16.8%-44.1%), respectively. SBRT-related acute adverse events and late adverse events ≥ G3 were reported in 6.5% (n = 2, including one G5 pneumonitis in a patient with prior interstitial lung disease) and 19.4% (n = 6, including one lethal hemoptysis after a lung biopsy in a patient receiving anticoagulants), respectively. CONCLUSIONS: The LungTech trial suggests that SBRT with 8 × 7.5Gy for central lung tumors in inoperable patients is associated with acceptable local control rates. However, late severe adverse events may occur after completion of treatment. This SBRT regimen is a viable treatment option after a thorough risk-benefit discussion with patients. To minimize potentially fatal toxicity, careful management of dose constraints, and post-SBRT interventions is crucial.

Bladder Cancer Radiation Oncology of the Future: Prognostic Modelling, Radiomics, and Treatment Planning With Artificial Intelligence.

Machine learning (ML) and artificial intelligence (AI) have demonstrated potential to improve the care of radiation oncology patients. Here we review recent advances applicable to the care of bladder cancer, with an eye towards studies that may suggest next steps in clinical implementation. Algorithms have been applied to clinical records, pathology, and radiology data to generate accurate predictive models for prognosis and clinical outcomes. AI has also shown increasing utility for auto-contouring and efficient creation of workflows involving multiple treatment plans. As technologies progress towards routine clinical use for bladder cancer patients, we also discuss emerging methods to improve interpretability and reliability of algorithms.

Demystifying the Results of RTOG 0617: Identification of Dose Sensitive Cardiac Subregions Associated With Overall Survival.

INTRODUCTION: The RTOG 0617 trial presented a worse survival for patients with lung cancer treated in the high-dose (74 Gy) arm. In multivariable models, radiation level and whole-heart volumetric dose parameters were associated with survival. In this work, we consider heart subregions to explain the observed survival difference between radiation levels. METHODS: Voxel-based analysis identified anatomical regions where the dose was associated with survival. Bootstrapping clinical and dosimetric variables into an elastic net model selected variables associated with survival. Multivariable Cox regression survival models assessed the significance of dose to the heart subregion, compared with whole heart v5 and v30. Finally, the trial outcome was assessed after propensity score matching of patients on lung dose, heart subregion dose, and tumor volume. RESULTS: A total of 458 patients were eligible for voxel-based analysis. A region of significance (p < 0.001) was identified in the base of the heart. Bootstrapping selected mean lung dose, radiation level, log tumor volume, and heart region dose. The multivariable Cox model exhibited dose to the heart region (p = 0.02), and tumor volume (p = 0.03) were significantly associated with survival, and radiation level was not significant (p = 0.07). The models exhibited that whole heart v5 and v30 were not associated with survival, with radiation level being significant (p < 0.05). In the matched cohort, no significant survival difference was seen between radiation levels. CONCLUSIONS: Dose to the base of the heart is associated with overall survival, partly removing the radiation level effect, and explaining that worse survival in the high-dose arm is owing, in part, to the heart subregion dose. By defining a heart avoidance region, future dose escalation trials may be feasible.

Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence.

Purpose: For patients receiving lung stereotactic ablative radiotherapy (SABR), evidence suggests that high peritumor density predicts an increased risk of microscopic disease (MDE) and local-regional failure, but only if there is low or heterogenous incidental dose surrounding the tumor (GTV). A data-mining method (Cox-per-radius) has been developed to investigate this dose-density interaction. We apply the method to predict local relapse (LR) and regional failure (RF) in patients with non-small cell lung cancer. Methods: 199 patients treated in a routine setting were collated from a single institution for training, and 76 patients from an external institution for validation. Three density metrics (mean, 90th percentile, standard deviation (SD)) were studied in 1mm annuli between 0.5cm inside and 2cm outside the GTV boundary. Dose SD and fraction of volume receiving less than 30Gy were studied in annuli 0.5-2cm outside the GTV to describe incidental MDE dosage. Heat-maps were created that correlate with changes in LR and RF rates due to the interaction between dose heterogeneity and density at each distance combination. Regions of significant improvement were studied in Cox proportional hazards models, and explored with and without re-fitting in external data. Correlations between the dose component of the interaction and common dose metrics were reported. Results: Local relapse occurred at a rate of 6.5% in the training cohort, and 18% in the validation cohort, which included larger and more centrally located tumors. High peritumor density in combination with high dose variability (0.5 - 1.6cm) predicts LR. No interactions predicted RF. The LR interaction improved the predictive ability compared to using clinical variables alone (optimism-adjusted C-index; 0.82 vs 0.76). Re-fitting model coefficients in external data confirmed the importance of this interaction (C-index; 0.86 vs 0.76). Dose variability in the 0.5-1.6 cm annular region strongly correlates with heterogeneity inside the target volume (SD; ρ = 0.53 training, ρ = 0.65 validation). Conclusion: In these real-world cohorts, the combination of relatively high peritumor density and high dose variability predicts increase in LR, but not RF, following lung SABR. This external validation justifies potential use of the model to increase low-dose CTV margins for high-risk patients.

Low muscle mass measured at T12 is a prognostic biomarker in unresectable oesophageal cancers receiving chemoradiotherapy.

BACKGROUND AND PURPOSE: Low muscle mass is an imaging biomarker of patient frailty that has been associated with increased toxicity and decreased survival in a number of cancers. Patients with unresectable oesophageal cancer receive chemoradiotherapy as standard of care. Muscle mass is not yet an established prognostic marker in this population. Muscle mass is usually assessed by segmenting skeletal muscle at the L3 vertebral level. But radiotherapy planning scans for oesophageal cancers do not always image this level, which has limited previous studies of body composition. Skeletal muscle is known to regulate immune function, but the association of muscle mass with lymphopenia in cancer patients has not been shown. MATERIALS AND METHODS: We retrospectively analyse 135 oesophageal cancer patients who received chemoradiotherapy and investigate the prognostic value of skeletal muscle area assessed at T12. We also examine the association between muscle mass and radiation-induced lymphopenia. RESULTS: We find that low muscle mass is associated with poorer overall survival (hazard ratio [95% confidence interval]: 0.72 [0.53-0.97]). However, this effect interacts with body mass index (BMI) such that the prognostic value of low muscle mass is removed by high BMI. In our study, patients with low muscle mass were more prone to radiation-induced lymphopenia (75% vs. 50% in patients with high muscle mass). A significant decrease in circulating lymphocytes was associated with poorer overall survival (hazard ratio [95% confidence interval]: 0.68 [0.47-0.99]). CONCLUSION: Our study shows that assessing muscle mass at T12 is feasible and provides prognostic information. Low muscle mass at T12 is associated with poorer overall survival and increased risk of radiation-induced lymphopenia. Muscle mass provides additional information over performance status and BMI. Low BMI patients are most affected by low muscle mass, highlighting the importance of close nutritional support in this population.

Feasibility of using a dual isocentre technique for treating cervical cancer on the 1.5 T MR-Linac.

Objective.Patients treated for cervical cancer exhibit large inter and intra-fraction anatomical changes. The Unity MR-Linac (MRL) can image these patients with MR prior to and during treatment which enables daily plan adaptation. However, the MRL has a limited treatment field in the sup/inf direction of 22 cm which can restrict the treatment of patients who require longer treatment fields. Here we explore potential adaptive workflows in combination with a dual isocentre approach, to widen the range of cervix patients that can benefit from this treatment.Approach.Ten cervical cancer patients were retrospectively planned with a dual isocentre technique to deliver 45 Gy in 25 fractions. 5 node-negative and 5 node-positive patients were planned using the EMBRACE II protocol. A 2 cm overlap region between the two isocentres was positioned entirely in the nodal region. A treatment workflow was simulated to account for inter-fraction anatomical change. Isocentre shifts of 3 and 6 mm were applied to investigate the effect of intra-fraction motion.Main results.Dual isocentre adapted plans ensured significantly better coverage than non-adapted (recalculated) plans with a larger benefit seen for the node-negative cases. The difference to the reference plan for the V4275 cGy to the ITV was -0.8 cGy and -8.2 cGy for the adapted and recalculated plans respectively. Movements superiorly did not affect the coverage of the ITV by more than 1%, but shifting it inferiorly caused the ITV coverage on the plan to reduce by ∼2.4% per mm.Significance.A dual isocentre technique for cervical cancer treatments and adaptive workflows have been demonstrated to recover the required plan quality for inter-fraction changes. This illustrates the feasibility of a dual isocentre technique for the MRL.

Spatial Gene Expression Changes in the Mouse Heart After Base-Targeted Irradiation.

PURPOSE: Radiation cardiotoxicity (RC) is a clinically significant adverse effect of treatment for patients with thoracic malignancies. Clinical studies in lung cancer have indicated that heart substructures are not uniformly radiosensitive, and that dose to the heart base drives RC. In this study, we aimed to characterize late changes in gene expression using spatial transcriptomics in a mouse model of base regional radiosensitivity. METHODS AND MATERIALS: An aged female C57BL/6 mouse was irradiated with 16 Gy delivered to the cranial third of the heart using a 6 × 9 mm parallel opposed beam geometry on a small animal radiation research platform, and a second mouse was sham-irradiated. After echocardiography, whole hearts were collected at 30 weeks for spatial transcriptomic analysis to map gene expression changes occurring in different regions of the partially irradiated heart. Cardiac regions were manually annotated on the capture slides and the gene expression profiles compared across different regions. RESULTS: Ejection fraction was reduced at 30 weeks after a 16 Gy irradiation to the heart base, compared with the sham-irradiated controls. There were markedly more significant gene expression changes within the irradiated regions compared with nonirradiated regions. Variation was observed in the transcriptomic effects of radiation on different cardiac base structures (eg, between the right atrium [n = 86 dysregulated genes], left atrium [n = 96 dysregulated genes], and the vasculature [n = 129 dysregulated genes]). Disrupted biological processes spanned extracellular matrix as well as circulatory, neuronal, and contractility activities. CONCLUSIONS: This is the first study to report spatially resolved gene expression changes in irradiated tissues. Examination of the regional radiation response in the heart can help to further our understanding of the cardiac base's radiosensitivity and support the development of actionable targets for pharmacologic intervention and biologically relevant dose constraints.

Dose outside of the prostate is associated with improved outcomes for high-risk prostate cancer patients treated with brachytherapy boost.

Background: One in three high-risk prostate cancer patients treated with radiotherapy recur. Detection of lymph node metastasis and microscopic disease spread using conventional imaging is poor, and many patients are under-treated due to suboptimal seminal vesicle or lymph node irradiation. We use Image Based Data Mining (IBDM) to investigate association between dose distributions, and prognostic variables and biochemical recurrence (BCR) in prostate cancer patients treated with radiotherapy. We further test whether including dose information in risk-stratification models improves performance. Method: Planning CTs, dose distributions and clinical information were collected for 612 high-risk prostate cancer patients treated with conformal hypo-fractionated radiotherapy, intensity modulated radiotherapy (IMRT), or IMRT plus a single fraction high dose rate (HDR) brachytherapy boost. Dose distributions (including HDR boost) of all studied patients were mapped to a reference anatomy using the prostate delineations. Regions where dose distributions significantly differed between patients that did and did-not experience BCR were assessed voxel-wise using 1) a binary endpoint of BCR at four-years (dose only) and 2) Cox-IBDM (dose and prognostic variables). Regions where dose was associated with outcome were identified. Cox proportional-hazard models with and without region dose information were produced and the Akaike Information Criterion (AIC) was used to assess model performance. Results: No significant regions were observed for patients treated with hypo-fractionated radiotherapy or IMRT. Regions outside the target where higher dose was associated with lower BCR were observed for patients treated with brachytherapy boost. Cox-IBDM revealed that dose response was influenced by age and T-stage. A region at the seminal vesicle tips was identified in binary- and Cox-IBDM. Including the mean dose in this region in a risk-stratification model (hazard ratio=0.84, p=0.005) significantly reduced AIC values (p=0.019), indicating superior performance, compared with prognostic variables only. The region dose was lower in the brachytherapy boost patients compared with the external beam cohorts supporting the occurrence of marginal misses. Conclusion: Association was identified between BCR and dose outside of the target region in high-risk prostate cancer patients treated with IMRT plus brachytherapy boost. We show, for the first-time, that the importance of irradiating this region is linked to prognostic variables.

Cardiac Function Modifies the Impact of Heart Base Dose on Survival: A Voxel-Wise Analysis of Patients With Lung Cancer From the PET-Plan Trial.

INTRODUCTION: Heart dose has emerged as an independent predictor of overall survival in patients with NSCLC treated with radiotherapy. Several studies have identified the base of the heart as a region of enhanced dose sensitivity and a potential target for cardiac sparing. We present a dosimetric analysis of overall survival in the multicenter, randomized PET-Plan trial (NCT00697333) and for the first time include left ventricular ejection fraction (EF) at baseline as a metric of cardiac function. METHODS: A total of 205 patients with inoperable stage II or III NSCLC treated with 60 to 72 Gy in 2 Gy fractions were included in this study. A voxel-wise image-based data mining methodology was used to identify anatomical regions where higher dose was significantly associated with worse overall survival. Univariable and multivariable Cox proportional hazards models tested the association of survival with dose to the identified region, established prognostic factors, and baseline cardiac function. RESULTS: A total of 172 patients remained after processing and censoring for follow-up. At 2-years posttreatment, a highly significant region was identified within the base of the heart (p < 0.005), centered on the origin of the left coronary artery and the region of the atrioventricular node. In multivariable analysis, the number of positron emission tomography-positive nodes (p = 0.02, hazard ratio = 1.13, 95% confidence interval: 1.02-1.25) and mean dose to the cardiac subregion (p = 0.02, hazard ratio = 1.11 Gy-1, 95% confidence interval: 1.02-1.21) were significantly associated with overall survival. There was a significant interaction between EF and region dose (p = 0.04) for survival, with contrast plots revealing a larger effect of region dose on survival in patients with lower EF values. CONCLUSIONS: This work validates previous image-based data mining studies by revealing a strong association between dose to the base of the heart and overall survival. For the first time, an interaction between baseline cardiac health and heart base dose was identified, potentially suggesting preexisting cardiac dysfunction exacerbates the impact of heart dose on survival.

Voxel-based analysis: Roadmap for clinical translation.

Voxel-based analysis (VBA) allows the full, 3-dimensional, dose distribution to be considered in radiotherapy outcome analysis. This provides new insights into anatomical variability of pathophysiology and radiosensitivity by removing the need for a priori definition of organs assumed to drive the dose response associated with patient outcomes. This approach may offer powerful biological insights demonstrating the heterogeneity of the radiobiology across tissues and potential associations of the radiotherapy dose with further factors. As this methodological approach becomes established, consideration needs to be given to translating VBA results to clinical implementation for patient benefit. Here, we present a comprehensive roadmap for VBA clinical translation. Technical validation needs to demonstrate robustness to methodology, where clinical validation must show generalisability to external datasets and link to a plausible pathophysiological hypothesis. Finally, clinical utility requires demonstration of potential benefit for patients in order for successful translation to be feasible. For each step on the roadmap, key considerations are discussed and recommendations provided for best practice.

The impact of continuously-variable dose rate VMAT on beam stability, MLC positioning, and overall plan dosimetry.

A recent control system update for Elekta linear accelerators includes the ability to deliver volumetric-modulated arc therapy (VMAT) with continuously variable dose rate (CVDR), rather than a number of fixed binned dose rates (BDR). The capacity to select from a larger range of dose rates allows the linac to maintain higher gantry speeds, resulting in faster, smoother deliveries. The purpose of this study is to investigate two components of CVDR delivery - the increase in average dose rate and gantry speed, and a determination of their effects on beam stability, MLC positioning, and overall plan dosimetry. Initially, ten VMAT plans (5 prostate, 5head and neck) were delivered to a Delta4 dosimetric phantom using both the BDR and CVDR systems. The plans were found to be dosimetrically robust using both delivery methods, although CVDR was observed to give higher gamma pass rates at the 2%/2 mm gamma level for prostates (p < 0.01). For the dual arc head-and-neck plans, CVDR delivery resulted in improved pass rates at all gamma levels (2%/2 mm to 4%/4 mm) for individual arc verifications (p < 0.01), but gave similar results to BDR when both arcs were combined. To investigate the impact of increased gantry speed on MLC positioning, a dynamic leaf-tracking tool was developed using the electronic portal imaging device (EPID). Comparing the detected MLC positions to those expected from the plan, CVDR was observed to result in a larger mean error compared to BDR (0.13 cm and 0.06 cm, respectively, p < 0.01). The EPID images were also used to monitor beam stability during delivery. It was found that the CVDR deliveries had a lower standard deviation of the gun-target (GT) and transverse (AB) profiles (p < 0.01). This study has determined that CVDR may offer a dosimetric advantage for VMAT plans. While the higher gantry speed of CVDR appears to increase deviations in MLC positioning, the relative effect on dosimetry is lower than the positive impact of a flatter and more stable beam profile.

Radial Data Mining to Identify Density-Dose Interactions That Predict Distant Failure Following SABR.

Purpose: Lower dose outside the planned treatment area in lung stereotactic radiotherapy has been linked to increased risk of distant metastasis (DM) possibly due to underdosage of microscopic disease (MDE). Independently, tumour density on pretreatment computed tomography (CT) has been linked to risk of MDE. No studies have investigated the interaction between imaging biomarkers and incidental dose. The interaction would showcase whether the impact of dose on outcome is dependent on imaging and, hence, if imaging could inform which patients require dose escalation outside the gross tumour volume (GTV). We propose an image-based data mining methodology to investigate density-dose interactions radially from the GTV to predict DM with no a priori assumption on location. Methods: Dose and density were quantified in 1-mm annuli around the GTV for 199 patients with early-stage lung cancer treated with 60 Gy in 5 fractions. Each annulus was summarised by three density and three dose parameters. For parameter combinations, Cox regressions were performed including a dose-density interaction in independent annuli. Heatmaps were created that described improvement in DM prediction due to the interaction. Regions of significant improvement were identified and studied in overall outcome models. Results: Dose-density interactions were identified that significantly improved prediction for over 50% of bootstrap resamples. Dose and density parameters were not significant when the interaction was omitted. Tumour density variance and high peritumour density were associated with DM for patients with more cold spots (less than 30-Gy EQD2) and non-uniform dose about 3 cm outside of the GTV. Associations identified were independent of the mean GTV dose. Conclusions: Patients with high tumour variance and peritumour density have increased risk of DM if there is a low and non-uniform dose outside the GTV. The dose regions are independent of tumour dose, suggesting that incidental dose may play an important role in controlling occult disease. Understanding such interactions is key to identifying patients who will benefit from dose-escalation. The methodology presented allowed spatial dose-density interactions to be studied at the exploratory stage for the first time. This could accelerate the clinical implementation of imaging biomarkers by demonstrating the impact of incidental dose for tumours of varying characteristics in routine data.